generate data for logistic regression simple question

Hi there,

If I want to see how good can I estimate the coefs in the simple linear model y=b0+b1*x+e when X follows exponential with mean 3 (or whatever), and e is normal(0,10^2) I do the following algorithm:

STEP 1: I produce (say 100) numbers from N(0,10^2), i.e. "e"

STEP 2: I produce 100 numbers from exponential, i.e. "x"

STEP 3: I obtain y, using the equation y=20+3*x+e.

STEP 4: I have my data {y,x}. I apply regression and get the estimates of b0 and b1.

I want to do the same procedure for a logistic model. (Any example will do as long as I understand the procedure)

What I suppose is:

STEP 1: I produce 100 numbers from exponential

STEP 2: Produce 100 numbers between (-20,20)

STEP 3: Do the calculation p=exp(0.1+0.3*x)/(1+exp(0.1+0.3*x)) and get 100 p's

STEP 4: Produce each response Y from bernoulli with parameter p(i), i=1,2,...100.

And I have my data {Y,X} and I apply logistic regression and estimate b0,b1. But this doesn't seem to work.

Can anyone help me?? Thanks in advance!!
Sorry guys but the algorithm for the logistic regression is working fine (forget step one, I typed it wrong),

Thanks and sorry if I wasted anyone's time..